Triple

T21270496
Position Surface form Disambiguated ID Type / Status
Subject Final Destination 2 E524242 entity
Predicate hasMainCharacter P1183 FINISHED
Object Officer Thomas Burke NE NERFINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Officer Thomas Burke | Statement: [Final Destination 2, hasMainCharacter, Officer Thomas Burke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Officer Thomas Burke
Context triple: [Final Destination 2, hasMainCharacter, Officer Thomas Burke]
  • A. Officer Francis Muldoon
    Officer Francis Muldoon is a bumbling yet well-meaning New York City police officer character from the 1960s television sitcom "Car 54, Where Are You?"
  • B. Officer John Hunton
    Officer John Hunton is the main police detective protagonist in the 1995 horror film "The Mangler," who investigates a series of gruesome deaths linked to a possessed industrial laundry machine.
  • C. Officer Frank Smith
    Officer Frank Smith is a fictional Los Angeles police officer who serves as Sergeant Joe Friday’s partner in the classic American crime drama series "Dragnet."
  • D. Officer Tom Turcotte
    Officer Tom Turcotte is a fictional police officer featured as a character in the television drama series "Boomtown."
  • E. Officer Bill Gannon
    Officer Bill Gannon is a fictional Los Angeles police officer and Joe Friday’s partner on the television series "Dragnet," portrayed by actor Harry Morgan.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Officer Thomas Burke
Target entity description: Officer Thomas Burke is a central character in the horror film "Final Destination 2," a police officer who becomes entangled in a deadly chain of premonitions and fatal accidents.
  • A. Officer Francis Muldoon
    Officer Francis Muldoon is a bumbling yet well-meaning New York City police officer character from the 1960s television sitcom "Car 54, Where Are You?"
  • B. Officer John Hunton
    Officer John Hunton is the main police detective protagonist in the 1995 horror film "The Mangler," who investigates a series of gruesome deaths linked to a possessed industrial laundry machine.
  • C. Officer Frank Smith
    Officer Frank Smith is a fictional Los Angeles police officer who serves as Sergeant Joe Friday’s partner in the classic American crime drama series "Dragnet."
  • D. Officer Tom Turcotte
    Officer Tom Turcotte is a fictional police officer featured as a character in the television drama series "Boomtown."
  • E. Officer Bill Gannon
    Officer Bill Gannon is a fictional Los Angeles police officer and Joe Friday’s partner on the television series "Dragnet," portrayed by actor Harry Morgan.
  • F. None of above. chosen

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73651c9208190a87d45acd6fafaaa completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:01 p.m.